With the rapid development of Internet technology, all kinds of mobile devices, device for the Internet of Things, such as various types of pads, smartphones, all kinds of wearable devices, robots, unmanned aerial vehicles, sensors and devices for the Internet of Things have become the fastest growing front-end devices accessing the Internet. The access to mobile devices is more than the ordinary desktop computer. For the sake of simplicity, all kinds of mobile devices, a device for the Internet of Things are collectively referred to as the mobile terminal device in the present invention. The pervasive computing and mobile cloud computing are main forms of future computing. However, all kinds of mobile devices, devices for the Internet of Things have the following differences from traditional desktop terminals. First, all kinds of mobile devices, devices for the Internet of Things are battery-powered and have limited energy. Second, since the computing capacity and storage capacity are limited by space, the scalability is low and the computing and storage capabilities are limited. Therefore, in the use of mobile devices, especially in the mobile front-end devices that support a variety of applications like smartphones and smart watches, there are some performance issues like shortened standby time, slow response to the operation, loss of user data, and limited functional expansion, which are caused due to limited resources and many other factors of the device after using for a period of time.
At present, the main solutions to these problems are as follows. The first solution is to install a system monitoring software on the mobile terminal equipment to remind, by scanning the mobile terminal equipment, the user to timely clear the system garbage and uninstall the software which is not used frequently. This is the mainstream method in the current market, but it still cannot solve the problem of user data loss, slow response to the operation, and limited function expansion. The second solution is the method of Cyber Foraging. The method of Cyber Foraging mainly solves the problem of how the cloud service can continue providing services seamlessly when the mobile device moves or when the mobile device is recharged after being out of power. A representative of the method is the Cloudlet system proposed by the Carnegie Mellon University. However, the system does not completely solve the problem of the shortened standby time, the slower response to the operation, and the limited functional expansion of the mobile terminal device. The third solution is the method of calculation and uninstallation. In the method of calculation and uninstallation, the operating situation of the mobile terminal equipment is mainly monitored, when the computing capacity and the related resources of mobile terminal equipment cannot meet the requirements of the program operation, the program is uninstalled to the cloud to complete the calculation task. For example, when the app running on the smartphone is uninstalled to the cloud to complete the computing task, the smartphone only shows the result of the computing. The method is mainly based on a virtual machine technology of the cloud computing, the representative methods and systems are ThinkAir, MAUI, CloneCloud, and so on. In these studies, function, class, object, method, or thread that is computationally heavy in the program on a mobile device is mainly uninstalled from the mobile device and installed on the cloud for execution to optimize the performance of the mobile device. Although this method can solve the performance issues of the current mobile terminal device, it is not commercially available yet. The main drawback is that the movement of the function, the class, the object, the method, or the thread inside the program involves the execution of mobile code, and the control is very complex. Moreover, there is a high requirement for the bandwidth and stability of the network environment, such that the cost of calculation and uninstallation need to be carefully evaluated and checked for mobile devices before the code is moved and during the execution of code movement. Controlling the complexity of evaluation can significantly increase the inherent overhead of a mobile device. Moreover, moving the code can cause serious security risks. The increased control overhead to guard against the security risks and the inherent control overhead will result in the unenforceable implementation of such mobile-based calculation and uninstallation method. The fourth solution is the method of Wechat applet, Android applet. The method uses the ideas of stream computing such as a transparent calculation of “leave after run out”, etc., to solve the problem of slow response to operation and limited functional expansion of the application software in mobile terminal devices. However, since both the Wechat applet and the Android applet belong to custom framework mode which combines the HTML5 and App programming in terms of the technical principle and the technical framework, the size of the program is strictly restricted, such that the applets can only replace some App having simple functions and cannot replace the App having slightly complicated functions.
No published literature and patent discloses a method for the mobile terminal device based on Android platform, which supports the APPs to efficiently operate in the mobile terminal device by a scheduling method combined with the background cloud service without limitation to the operation of the Apps. Both applet and general Android App are supported such that it is ensured that the operating performance of the mobile terminal device is always efficient, and the user experience is good.